AI tool comparison
Claude How To vs CodeBurn
Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.
Developer Tools
Claude How To
The missing practical guide to mastering Claude Code
75%
Panel ship
—
Community
Free
Entry
Claude How To fills the gap between Anthropic's feature documentation and what developers actually need to build real workflows with Claude Code. Where official docs describe what features exist, this repository shows how to combine slash commands, memory, subagents, hooks, and MCP servers into automated pipelines for code review, deployment, and documentation generation. The guide contains 10 tutorial modules with Mermaid diagrams, copy-paste configuration templates, and a progressive learning roadmap totaling 11–13 hours of structured content. Each module includes interactive self-assessment quizzes, and the entire guide is actively maintained to track Claude Code releases—currently synced to v2.2.0. Over 25 hook event types are documented with working examples, and there's a complete CLI reference for headless automation in CI/CD pipelines. Built by luongnv89 and released with an MIT license, Claude How To climbed to 18k stars in its first week—mostly organically through HN and X shares from developers frustrated with scattered official documentation. It represents the kind of community-built learning infrastructure that often outlasts the tools it documents.
Developer Tools
CodeBurn
Track and cut your AI coding spend across every tool you use
75%
Panel ship
—
Community
Paid
Entry
CodeBurn is a terminal TUI dashboard that reads AI coding session data directly from disk — no API keys, proxies, or wrappers required — and surfaces a breakdown of token costs across Claude Code, Codex, Cursor, GitHub Copilot, and more. It auto-classifies activity into 13 categories (coding, debugging, testing, refactoring, etc.) and shows one-shot success rates per task type, giving developers a rare look at where their AI spend actually goes. The dashboard includes gradient charts, keyboard navigation, multiple time periods, and a currency converter supporting 162 ISO 4217 currencies. There's also an "optimize" command that scans sessions for waste patterns and outputs actionable, copy-paste fixes. For teams, a macOS menu bar app surfaces daily costs at a glance. With 2.7k stars after a Show HN post, CodeBurn clearly scratched a real itch. As AI coding budgets scale from hundreds to thousands of dollars per developer per month, tooling that makes costs visible and actionable becomes less optional and more essential.
Reviewer scorecard
“The hook event documentation alone is worth bookmarking—25+ events with working examples is something the official docs simply don't have. The CLI headless automation reference for CI/CD is genuinely useful and hard to find elsewhere.”
“This is exactly the observability layer AI coding has been missing. Knowing that 40% of my Claude Code tokens went to a single poorly-scoped context window is the kind of insight that pays for itself in the first week. The 'optimize' command is genuinely useful, not just marketing copy.”
“Community documentation guides have a well-documented half-life: they go stale fast and create confusion when they drift from the actual tool behavior. The promise to 'sync with every Claude Code release' is optimistic given it's a one-person side project. Anthropic's own docs will eventually improve, making this redundant.”
“The multi-provider claim is impressive on paper, but Cursor and Copilot don't expose session data the same way Claude Code does. Expect incomplete data for non-Anthropic tools until the provider ecosystem standardizes telemetry formats. Also: if your team uses ephemeral dev containers, good luck getting disk reads to work.”
“The fact that a community guide to using an AI tool hit 18k stars in a week tells you everything about the documentation debt the AI industry has accumulated. Claude How To is a symptom of a real problem—and a useful one while the official ecosystem catches up.”
“Cost observability is the missing infrastructure layer for the AI-native development era. Just as APM tools like Datadog became mandatory once cloud costs mattered, AI coding cost tracking will be table stakes within 18 months. CodeBurn is an early mover in a category that will consolidate around one or two dominant players.”
“The structured learning path with time estimates is a thoughtful design choice—most technical guides dump everything on you at once. Knowing upfront that advanced MCP configuration takes 5 hours lets you plan your learning rather than falling into a rabbit hole.”
“The TUI design is clean and keyboard-navigable in a way most developer dashboards aren't. Gradient charts inside a terminal window sounds tacky but actually reads well. The category breakdown would make a genuinely compelling weekly standup artifact for teams trying to improve AI workflow discipline.”
Weekly AI Tool Verdicts
Get the next comparison in your inbox
New AI tools ship daily. We compare them before you waste an afternoon.